Home > Publications database > Simulation and Optimizationof a Position Sensitive ScintillationDetector with Wavelength ShiftingFibers for Thermal Neutrons |
Book/Report/Dissertation / PhD Thesis | FZJ-2017-03549 |
2016
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
Jülich
Please use a persistent id in citations: http://hdl.handle.net/2128/14845
Report No.: Juel-4397
Abstract: Due to the worldwide shortage of 3He and the price development caused by this, alternativeconcepts of neutron detection are in demand. One possible alternative is aZnS/LiF scintillation detector with readout via wavelength shifting fibers. The presenteddissertation describes the development of a model of the physical frontend, which enablescomputer-aided simulations with different configurations and conditions.The model regards the microscopic structure of the scintillator during the trackingof alpha and triton particles created by the conversion of a neutron at a 6Li as well asthe propagation of photons through the scintillator plate. In the first case, the structureis simulated via randomly placed spherical grains, through which the charged secondaryparticles are tracked. In the second case, the photons are subject to a random walk withparameters dependend on the composition of the scintillator.The model is validated in several steps, during which single aspects of the model areverified. There is a good agreement between measurements and simulations of neutronabsorption and pulse height spectra of different scintillator samples.A comparison with optical transmission measurements shows, that the simulated effectiveoptical absorption coefficent is of the same order of magnitude as the measuredvalue of samples of one manufacturer, but is smaller by a factor of 6 than the value ofsamples of another manufacturer.For the validation of the entire model, measurements of a prototype are compared tosimulations. In order to compare the data event-wise, a detection algorithm based oncluster finding is developed. Measurements and simulations are in good agreement, so themodel can be regarded as validated.To optimize multiple parameters at the same time, a generalization of the GoldenSection Search can be used. This algorithm optimizes parameters with respect to an optimizationfunction, e.g. detection effciency, which is calculated dependend on simulationdata. This way it is possible to optimize detector parameters for new developments.
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